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python/gtsam/tests/test_NonlinearOptimizer.py

@@ -15,11 +15,12 @@ from __future__ import print_function
 import unittest
 
 import gtsam
-from gtsam import (DoglegOptimizer, DoglegParams, DummyPreconditionerParameters,
-                   GaussNewtonOptimizer, GaussNewtonParams, GncLMParams, GncLossType,
-                   GncLMOptimizer, LevenbergMarquardtOptimizer, LevenbergMarquardtParams,
-                   NonlinearFactorGraph, Ordering, PCGSolverParameters, Point2,
-                   PriorFactorPoint2, Values)
+from gtsam import (
+    DoglegOptimizer, DoglegParams, DummyPreconditionerParameters, GaussNewtonOptimizer,
+    GaussNewtonParams, GncLMParams, GncLossType, GncLMOptimizer, LevenbergMarquardtOptimizer,
+    LevenbergMarquardtParams, NonlinearFactorGraph, Ordering, PCGSolverParameters, Point2,
+    PriorFactorPoint2, Values
+)
 from gtsam.utils.test_case import GtsamTestCase
 
 KEY1 = 1
@@ -28,7 +29,6 @@ KEY2 = 2
 
 class TestScenario(GtsamTestCase):
     """Do trivial test with three optimizer variants."""
-
     def setUp(self):
         """Set up the optimization problem and ordering"""
         # create graph
@@ -154,11 +154,13 @@ class TestScenario(GtsamTestCase):
         iteration_count = 0
         final_error = 0
         final_values = None
+
         def iteration_hook(iter, error_before, error_after):
             nonlocal iteration_count, final_error, final_values
             iteration_count = iter
             final_error = error_after
             final_values = optimizer.values()
+
         # optimize
         params = LevenbergMarquardtParams.CeresDefaults()
         params.setOrdering(self.ordering)
@@ -170,5 +172,6 @@ class TestScenario(GtsamTestCase):
         self.assertEqual(self.fg.error(actual), final_error)
         self.assertEqual(optimizer.iterations(), iteration_count)
 
+
 if __name__ == "__main__":
     unittest.main()